City of Garland, GIS Department

In collaboration with the city works department, drawing symbols were developed to communicate the size and type of connections while preserving the integrity of the geometric network.

The map shows drive times for 3 proposed sites for fire stations in Garland. In addition to this study, drive times around existing fire stations were also developed to evaluate any gaps in service or coverage. Drive-time analysis was developed by creating service areas and setting the parameters for Travel Mode restrictions: Trucking Time to accommodate larger emergency vehicles, a slower maximum speed to accommodate speed limitations for larger vehicles, and traffic regulations for emergency vehicles. 

In this project, a pre-trained ESRI deep learning (DL) model is used to detect swimming pools in the City of Garland within an area consisting of 56 homes. The Object Detection tool from the Deep Learning Toolbox is used. For the area shown, the model ran for approximately 30 minutes and detected 5 swimming pools. 

This project identified high-density areas of low-cost housing in the City of Garland. The Kernel Density tool creates a density mapping of home values under $250K and $200K. Next, the Contour List tool uses a calculated contour interval to only demarcate the target area. 

Rental property data for single homes was used to find the percentage of rental properties in each Council District and Block Group. In addition, heat mapping and hotspot analysis were used to identify statistically significant clusters of high or low-density areas of rental properties. 

The Traffic Grant Zones were updated and printed for use by the Police Department.

Housing sales contract information is downloaded in spreadsheet format. Houses are geocoded to the correct address, and then the geocoded data is appended to the hosted database.